Opioids are the cornerstone of treatment for moderate to severe acute and chronic pain, which costs the US economy tens of billions of dollars annually. However, the dose of opioid required to control pain varies up to 10-fold between individuals. In addition, large inter-individual differences exist in the degree to which patients suffer side effects from opioids such as sedation, pruritus, or nausea. Moreover, it is not known why some individuals become addicted to opioids while others do not. The principal hypothesis to be evaluated is that the degree of analgesia provided by opioids in humans displays substantial familial aggregation, and is, in fact, heritable. These studies will use a classical twin paradigm to determine the role of genetics and the environment in influencing analgesia and a range of other opioid effects. Specific Aims: (1) Determine the degree to which opioid analgesic responses show familial aggregation and make preliminary estimates of heritability using both a heat pain model and a model of inflammatory pain with central sensitization. (2) Determine the degree to which non- analgesic opioid responses show familial aggregation and make preliminary estimates of heritability. Side effects such as sedation, nausea, respiratory depression, and pruritus, as well as the positive affective response, a measure of abuse potential, will be monitored. Monozygotic (MZ) and dizygotic (DZ) twin pairs (125 total pairs) will be tested under controlled pain laboratory conditions for their responses to opioid infusion using the complementary pain models while monitoring side effects and additional psychometric indices of mood, sleep, and abuse potential. The selected models provide unique mechanistic information because they involve different peripheral and/or central pain pathways. DNA samples will be collected for zygosity testing and banked for future studies. PUBLIC HEALTH RELEVANCE: Establishing a significant heritable component to human responses to opioids could lead to new analgesic strategies tailored to an individual's genetic makeup, thus reducing patient risk and speeding control of pain. In addition, future large scale candidate gene and genome wide association studies based on these results could uncover key genes involved in pain and analgesic pathways, leading to more rational therapeutic targeting and ultimately more cost- effective treatments.